Bad Data Detection Method in Power System State Estimation

전력계통 상태 추정에서의 불량정보 검출기법

This paper presents a algorithm to improve accuracy and reliability in state estimation of contaminated bad data. The conventional algorithms for detection of bad data confront the problems of excessive memory requirements and long computation time. In order to overcome measurement compensation approach is proposed to reduce computation time and partitioned measurement error model has the advantage of remarkable reduction in computation time and memory requirements in estimated error computation. The proposed algorithm has been tested for IEEE sample systems, which shows its applicability to on-line power systems.